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When someone you care about needs help, help them. Even when you have other things to do, help them anyway.

When people ask you for help, it’s a sign they trust you. And they trust you because you’ve demonstrated over time that your words and behaviors match. You said you’d do A and you did A. You said you’d do B and you did B. And because you’ve made that investment in them over the years, they value you and your time. And because they value you and your time, they don’t want to be a burden to you. And if they think you’ve got a lot on your plate, they may downplay the importance of their need for help and say things like “It’s no big deal.” or “It’s not that important.” or “It’s okay, it can wait.”.

However unforcefully, they asked for help because the need it. It was a big deal for them to ask because they know you are busy. And their willingness to dismiss or delay, is not a sign of unimportance of their need. Rather, it’s a show of their respect for you and your time. They desperately need your help, but care enough about you to give you any opportunity to say no. Those are the telltale signs that it’s time to stop what you’re doing and help them. This is the time when you can make the biggest difference. Stop immediately and help them.

Your helping starts with listening and listening starts with getting ready to listen. Smile and tell them that this little chat deserves a coffee or cold drink and walk with them to get a beverage. This critical step serves several functions. It makes it clear you are willing to make time for them and puts them at ease; it gives you time to let go of what you were working on so you can give them your full attention; and it gives you a little time to put yourself in their shoes so you will be able to hear what really going on.

By making time for them, you’ve already helped them. Someone they trust and respect stopped what they were doing and made time for them. They’re already standing two inches taller. And, with a clear head, you actively listen and understand, they grow another two inches. Often, just telling their story is enough for them to solve their own problem. In that way, your helping starts and ends with listening. And other times, they don’t really want you to solve their problem, they just want you to listen and empathize. And when they’re looking for more, rather than giving them answers, they’d rather you ask clarifying questions and paraphrase to demonstrate understanding.

You can’t do this for everyone, but you can do it for the people you care about most. Sure, you have to scamper to catch up on your own work, but it’s worth it. By helping them you help yourself twice – once from happiness that comes from helping someone you care about and twice from the joy that comes from watching them do the same for people they care about.

Our work is difficult and our lives are busy. But our work gets easier when we get and give help. And even with our always-on, always-connected culture, life is about building meaningful connections. How can your life be too busy for that?

Maybe we have it backwards. What if meaningful connections aren’t something we create so we can do our work better? What if we think of work as nothing more than a mechanism to create meaningful connections?

As a technologist it’s important to know the maturity of a technology. Like people, technologies are born, they become children, then adolescents, then adults and then they die. And like with people, the character and behavior of technologies change as they grown and age. A fledgling technology may have a lot of potential, but it can’t pay the mortgage until it matures. To know a technologies level of maturity is to know when it’s premature to invest, to know when it’s time to invest, to know when to ride it for all it’s worth and time to let it go.

Google has a tool called Ngram Viewer that performs keyword searches of a vast library of books and returns a plot of how frequently the word was found in the books. Just type the word in the search line, specify the years (1800-2007) and look at the graph.

Below is a graph I created for three words: locomotive, automobile and airplane. (Link to graph.) If each word is assumed to represent a technology, the graph makes it clear when authors started to write about the technologies (left is earliest) and how frequently it was used (taller is more prevalent). As a technology, locomotives came first, as they were mentioned in books as early as 1800. Next came the automobile which hit the books just before 1900. And then came the airplane which first showed itself in about 1915.

In the 1820s the locomotives were infants. They were slow, inefficient and unreliable. But over time they matured and replaced the Pony Express. In the late 1890s the automobiles were also infants and also slow, inefficient and unreliable. But as they matured, they displaced some of the locomotives. And the airplanes of 1915 were unsafe and barely flight-worthy. But over time they matured and displaced the automobiles for the longest trips.

[Side note – the blip in use of the word in 1940s is probably linked to World War II.]

But for the locomotive, there’s a story with a story. Below is a graph I created for: steam locomotive, diesel locomotive and electric locomotive. After it matured in the 1840s and became faster and more efficient, the steam locomotive displaced the wagon trains. But, as technology likes to do, the electric locomotive matured several decades after it’s birth in 1880 and displaced it’s technological parent the steam locomotive. There was no smoke with the electric locomotive (city applications) and it did not need to stop to replenish it’s coal and water. And then, because turn-about is fair play, the diesel locomotive displaced some of the electric locomotives.

The Ngram Viewer tool isn’t used for technology development because books are published long after the initial technology development is completed and there is no data after 20o7. But, it provides a good example of how new technologies emerge in society and how they grow and displace each other.

To assess the maturity of the youngest technologies, technologists perform similar time-based analyses but on different data sets. Specialized tools are used to make similar graphs for patents, where infant technologies become public when they’re disclosed in the form of patents. Also, special tools are used to analyze the prevalence of keywords (i.e., locomotives) for scientific publications. The analysis is similar to the Ngram Viewer analysis, but the scientific publications describe the new technologies much sooner after their birth.

To know the maturity of the technology is to know when a technology has legs and when it’s time to invent it’s replacement. There’s nothing worse than trying to improve a mature technology like the diesel locomotive when you should be inventing the next generation Maglev train.

To meet ever-increasing growth objectives, established companies want to be more entrepreneurial. And the thinking goes like this – launch new products and services to create new markets, do it quickly and do it on a shoestring. Do that Lean Startup thing. Build minimum viable prototypes (MVPs), show them to customers, incorporate their feedback, make new MVPs, show them again, and then thoselaunch.

For software products, that may work well, largely because it takes little time to create MVPs, customers can try the products without meeting face-to-face and updating the code doesn’t take all that long. But for products and services that require new hardware, actual hardware, it’s a different story. New hardware takes a long time to invent, a long time to convert into an MVP, a long time to show customers and a long time to incorporate feedback. Creating new hardware and launching quickly in an entrepreneurial way don’t belong in the same sentence, unless there’s no new hardware.

For hardware, don’t think smartphones, think autonomous cars. And how’s that going for Google and the other software companies? As it turns out, it seems that designing hardware and software are different. Yes, there’s a whole lot of software in there, but there’s also a whole lot of new sensor systems (hardware). And, what complicates things further is that it’s all packed into an integrated system of subsystems where the hardware and software must cooperate to make the good things happen. And, when the consequences of a failure are severe, it’s more important to work out the bugs.

And that’s the rub with entrepreneurship and an established brand. For quick adoption, there’s strong desire to leverage the established brand – GM, Ford, BMW – but the output of the entrepreneurial work (new product or service) has to fit with the brand. GM can’t launch something that’s half-baked with the promise to fix it later. Ford can come out with a new app that is clunky and communicates intermittently with their hardware (cars) because it will reflect poorly on all their products. In short, they’ll sell fewer cars. And BMW can’t come out with an entrepreneurial all-electric car that handles poorly and is slow off the start. If they do, they’ll sell fewer cars. If you’re an established company with an established brand, the output of your entrepreneurial work must fit with the established brand.

If you’re a software startup, launch it when it’s half-baked and fix it later, as long as no one will die when it flakes out. And because it’s software, iterate early and often. And, there’s no need to worry about what it will do to the brand, because you haven’t created it yet. But if you’re a hardware startup, be careful not to launch before it’s ready because you won’t be able to move quickly and you’ll be stuck with your entrepreneurial work for longer than you want. Maybe, even long enough to sink the brand before it ever learned to swim. Developing hardware is slow. And developing robust hardware-software systems is far slower.

If you’re an established company with an established brand, tread lightly with that Lean Startup thing, even when it’s just software. An entrepreneurial software product that works poorly can take down the brand, if, of course, your brand stands for robust, predictable, value and safety. And if the entrepreneurial product relies on new hardware, be doubly careful. If it goes belly-up, it will be slow to go away and will put a lot of pressure on that wonderful brand you took so long to build.

If you’re an established brand, it may be best to buy your entrepreneurial products and services from the startups that took the risk and made it happen. That way you can buy their successful track record and stand it on the shoulders of your hard-won brand.

When it’s time to create something new, most people try to imagine the future and then put a plan together to make it happen. There’s lots of talk about the idealize future state, cries for a clean slate design or an edict for a greenfield solution. Truth is, that’s a recipe for disaster. Truth is, there is no such thing as a clean slate or green field. And because there are an infinite number of future states, it’s highly improbable your idealized future state is the one the universe will choose to make real.

To create something new, don’t look to the future. Instead, sit in the present and understand the system as it is. Define the major elements and what they do. Define connections among the elements. Create a functional diagram using blocks for the major elements, using a noun to name each block, and use arrows to define the interactions between the elements, using a verb to label each arrow. This sounds like a complete waste of time because it’s assumed that everyone knows how the current state system behaves. The system has been the backbone of our success, of course everyone knows the inputs, the outputs, who does what and why they do it.

I have created countless functional models of as-is systems and never has everyone agreed on how it works. More strongly, most of the time the group of experts can’t even create a complete model of the as-is system without doing some digging. And even after three iterations of the model, some think it’s complete, some think it’s incomplete and others think it’s wrong. And, sometimes, the team must run experiments to determine how things work. How can you imagine an idealized future state when you don’t understand the system as it is? The short answer – you can’t.

And once there’s a common understanding of the system as it is, if there’s a call for a clean sheet design, run away. A call for a clean sheet design is sure fire sign that company leadership doesn’t know what they’re doing. When creating something new it’s best to inject the minimum level of novelty and reuse the rest (of the system as it is). If you can get away with 1% novelty and 99% reuse, do it. Novelty, by definition, hasn’t been done before. And things that have never been done before don’t happen quickly, if they happen at all. There’s no extra credit for maximizing novelty. Think of novelty like ghost pepper sauce – a little goes a long way. If you want to know how to handle novelty, imagine a clean sheet design and do the opposite.

Greenfield designs should be avoided like the plague. The existing system has coevolved with its end users so that the system satisfies the right needs, the users know how to use the system and they know what to expect from it. In a hand-in-glove way, the as-is system is comfortable for end users because it fits them. And that’s a big deal. Any deviation from baseline design (novelty) will create discomfort and stress for end users, even if that novelty is responsible for the enhancement you’re trying to deliver. Novelty violates customer expectations and violating customer expectations is a dangerous game. Again, when you think novelty, think ghost peppers. If you want to know how to handle novelty, imagine a green field and do the opposite.

This approach is not incrementalism. Where you need novelty, inject it. And where you don’t need it, reuse. Design the system to maximize new value but do it with minimum novelty. Or, better still, offer less with far less. Think 90% of the value with 10% of the cost.

In business, the only direct lever to pull is resource allocation. The people are already on the books, just change what they work on. But pulling that off is difficult.

No need to wait for new hires, just move resources from one project to another. Stop project A and start project B. Simple, right? Not so much. Emotional attachment causes project A to defend their resources and project B to complain the resources haven’t moved. Resources will be slow to flow.

No need to take the time to develop new capability, just reassign capable resources from business 1 to business 2 and watch progress unfold. No problem, right? Wrong. There’s immense organizational drama from prioritizing one business over another. Again, the pace of resource flow will be glacial.

And with innovation, the drama is doubled. It’s threatening when resources flow from mainstream projects with tangible (but small) returns to more speculative projects with highly uncertain returns. But that’s what must happen.

If there’s a mismatch between the words and resource allocation, believe resource allocation.

If the innovation banners are plastered on all the walls and everyone has the tee shirt, yet the resources don’t flow to the innovation work, it’s an innovation farce. Run away. Here’s what the four HOWs of innovation look like through the lens of resource allocation.

How To Start. Define the yearly funding level for innovation resources that is independent of the yearly planning process. In short, create an innovation tax at a fixed percentage of revenue. This gets funded before anything else. It’s the pay-yourself-first approach to innovation. And when the money is allocated and the resources flow, there’s no need for banners and tee shirts. Alignment comes with the money.

Next, choose a leader to put in place standing processes to continuously funnel project ideas into a common hopper. One pile for all ideas – university research, mergers and acquisitions, voice of the technology, voice of the customer (direct observation and listening), patents and YouTube videos of purposeful misuse of your product.

How To Choose. Define funding levels across the various flavors of projects in the portfolio and set up a standing meeting for senior leaders to choose the best projects. This selection process is light on analysis and heavy on judgment, so allocate leaders who are not afraid to use good judgement. And set up a standing meeting with the CEO to pace the selection work (make sure senior leaders allocate their time.)

How To Execute. Internal, external, or partner, the work defines the right way to allocate resources. Based on the work, choose the right organization and the best leader and fully staff the project before considering a second project. The most popular failure mode is running too many projects in parallel and getting none done. The second popular failure mode forgetting to fund the support resources needed for innovation. Allocate money for tools, time, training and a teacher. Establish a standing meeting where senior leaders review the projects. This must be outside the review process normal projects.

How To Improve. No one ever allocates time to do this. To get the work done, trick the system and include the work as a standing agenda item in the How To Execute review meetings. Find a problem, fix a problem. Improve as you go.

Allocate the best resources to the best projects and make sure senior leaders allocate time to the innovation work. The best predictors of successful innovation are the character of the fully-staffed, fully-funded projects and the character of people that run them.

When the output cannot be predicted, that’s uncertainty. And if there’s one thing to be certain of it’s uncertainty is always part of the equation.

With uncertainty, the generally accepted practice is minimization, and the method of choice is to control inputs. The best example is a high volume manufacturing process where inputs are controlled to reduce variation of the output (or reduce the uncertainty around goodness). Six Sigma tightens the screws on suppliers, materials, process steps, assembly tools and measurement gear so the first car off the production line is the same as the last one. That way, customers are certain to get what they’re promised. Minimization of uncertainty makes a lot of sense in the manufacturing analogy.

But there’s no free lunch with uncertainty, and the price of all this control is inflexibility. The manufacturing process can do only what it’s designed to do – to make what it was designed to make – and no more. And it can provide certainty of output only over a finite input range. Within the appropriate range of inputs there is certainty, but outside that range there is uncertainty. Even in the most well defined, highly controlled processes where great expense is taken to reduce uncertainty, there is uncertainty. Even the best automotive assembly lines can be disrupted by things like tsunamis, earthquakes, epidemics and labor strikes (100% certainty doesn’t exist). But still, in the manufacturing context minimization of uncertainty is a sound strategy.

When the intent of a process is to do things that have never been done and to bring new things to life, minimization of uncertainty is directionally incorrect. Said a different way, creativity and innovation demand uncertainty. More clearly – if there’s no uncertainty in the trenches, there’s no innovation.

The manufacturing analogy has been pushed too far from the factory. Just as Six Sigma has eliminated variation (and uncertainty) from things it shouldn’t (creativity work), lean and its two uncertainty killers (best practices and standard work) have been jammed into the gears of innovation and gummed up the works.

Standard work and best practices were invented to reduce variation in how work is done with the objective of, you guessed it, reducing uncertainty. The idea is to continuously improve and converge on the right recipe (sequence of operations or process steps) so the work is done the same way every-day-all-day. By definition, innovation work (the process steps) is never done the same way twice. The rule with best practices is simple – it should be reused every time there’s a need for that exact process. That makes sense. But it makes no sense to use a best practice when a process is done for the first time.

[Okay, the purists say that all transactional elements of innovation should follow standard work, and theoretically that’s right. But practically, the backwash of standard work, even when applied to transactional work, infects the psyche of the innovator and reduces uncertainty where uncertainty should be bolstered.]

Uncertainty is an important part of innovation, but it should not be maximized (it’s as inappropriate as minimizing). And there is no best practice for calculating the right amount. To strike a good balance, hold onto the fact that uncertainty and flexibility are a matched pair, and when doing something for the first time flexibility is a friend. And when standard work and best practices are imposed in the name of innovation efficiency, remember it’s far more important to have innovation effectiveness.

A technology without a market is as valuable as a market without a technology – they’re both worthless. At one end of the spectrum you have something interesting running in the lab and at the other you have an interesting insight around a new market. But one won’t do, and from either end of the rainbow your quest is to find the pot of gold at the other end.

Scenario A – As a marketing leader you went out into the market, heard the unhearable, saw the unseeable and the gears of your mind gnashed and clunked until it brought into being a surprising insight. Now it’s time to come back to the technical community in search of a technology. For this clarity is key, but for technologists the voice of the customer is a foreign language, and worse, you’ve invented a new dialect.

Step 2. In front of the technologists mark up the existing marketing literature so it satisfies the surprising insight. (Think – same as the old product, but different.) Starting with something they know and building from there helps the technologists see the newness from the grounded context of existing products and technologies.

Step 3. Then, with the technologists, draw a hand sketch of the customer using the new product in a new way, then underneath the sketch write a single sentence that describes the valuable customer outcome (from the customer’s perspective).

Step 4. Together with the technologists define the new design elements of the prouct to make the product perform like the sketch and satisfy the valuable customer outcome.

Step 5. With the technologists go out to the lab and make a prototype of the new design element, bolt it on to an existing product platform and use the product in the manner described in your sketch. If it doesn’t work as it should, modify the prototype until it does.

Step 6. Take the prototype to the market and ask them if it delivers on the valuable customer outcome. If it doesn’t, modify the prototype until it does. And when it does, launch it.

Scenario B – As a technologist you went out into the lab, thought the unthinkable, pondered the impossible and the gears of your mind gnashed and clunked until it brought into being a surprising technology. Now it’s time to come back to the marketing community in search of a market. For this clarity is key, but for marketing the voice of the technology is a foreign language, and worse, like your counterpart in Scenario A, you’ve invented a new dialect.

Step 1. Dig up the product spec for an existing product that’s closest to your new technology.

Step 2. In front of the marketers mark up the product spec so it describes the functionality of the new technology. (Think – same as the old product, but different.) Starting with something they know and building from there helps the marketers see the newness from the grounded context of existing products and technologies.

Step 3. Again in front of the marketers, define the new elements of the technology that make the product perform like it does.

Step 4. With the marketers, draw a hand sketch of the customer using the new product in a new way, then underneath the sketch write a single sentence that describes the valuable customer outcome (from the customer’s perspective).

Step 5. Together with the marketers and the prototype go out to the field and let customers use it as THEY see fit. If they use it in the manner described in your sketch, you’ve identified a potential customer segment. If they don’t, modify the sketch and valuable outcome sentence until it matches their use, or seek out other customers who use it like the sketch.

Step 6. Decide on the most interesting product use and customer outcome, and take the prototype to the target customers. Ask them if it delivers on the valuable customer outcome. If it doesn’t, investigate different customer segments until it does. And when it does, launch it.

Scenarios A and B are contrived. In scenario A, product use and valuable customer outcomes are static and the technology changes to fit them. In Scenario B, it’s reversed – static technology and dynamic product use and customer outcomes. While the scenarios are helpful to see the work from two perspectives and define the end points, that’s not how it happens.

Innovation is always a clustered-jumble of the two scenarios. In fact it’s more like a double helix where the customer strand winds around the technology and the technology strand winds around the customer. One strand takes the lead and mutates the other, which, in turn, spirals learning in unforseen directions.

There’s no getting around it – market and technology co-evolve. There’s no best practice, there’s no best orgainizational structure, and breaking things down the smallest elements won’t get you there.

Instead of spending time and money sequencing the innovation genome, take your cue from nature – try stuff and do more of what worked and less of what didn’t.

And remember the cardinal rule – the organization with the best genes wins.

Your value proposition is aging and will soon die. No matter your value proposition, this is truth – no value proposition has ever made it out alive.

Your value proposition – what you deliver, the goodness you provide – is what has made you what you are, and that’s why you center your existence on its principles and that’s why it’s sticky. And that’s also why it’s too sticky. Your successful value proposition makes you feel good so you cling to it all costs. And when it’s on life support, when it can no longer breathe on its own, you grasp more desperately for its long past goodness. And when it’s flat-lined you hysterically grab for the paddles to shock it back to life. This is unskillful, but it’s how it goes.

Value propositions are impermanent – they’re born, they grown, they die. It’s best to recognize this truth and work within the impermanence. When a successful value proposition is almost through adolescence and is thinking of heading off to college, that’s the time to bring another one to life. You may be looking forward to being an empty nester, but that works with kids, not with value propositions.

Value propositions have a long gestation period, and you never really know how they’ll turn out until they mature, or they don’t. You may think you have a good idea how they’ll turn out when they get to kindergarten, but life is uncertain, and you don’t really know how things will go. You can’t predict; you can only decide to try, or not. But there’s hope.

There are several important lenses to squint through to improve your odds, but, before that there’s one rule to live by – all infant value propositions must be disruptive. If you’re going to invest all that time and energy, the payoff must be worth the effort – think diapers of disruption.

The lens of cost of entry. To distrupt, look to radically reduce the cost of entry. If you make capital equipment, come up with a way to provide value without the capital purchase. It could be financing terms, renting, leasing, power by the hour. It could be smaller, lower cost machines that do the job, but lets the customer buy smaller chunks of capacity. It could be new technology that radically reduces cost. Or, it could be my favorite – eliminating functionality and features so the product does less and costs a whole lot less. Or, figure out some non-traditional yet powerful blockers of entry and make them go away.

The lens of user decisions. This is a big one. Eliminate all the adjustments on your so you can sell your product to people who, today, don’t have the technical savvy to run them. Eliminate all words from your product, which will let you sell them to folks that cannot read your language. Design your product with a green light and a red light, and when the red light is on, your product emails someone letting them know the failure mode and also automatically reorders the replacement parts. Add sensors to your product so it reconfigures itself so the user gets more value.

The lean lens. If you make big machines that create batching, right-size them. Look at your customer’s value stream and try to change your product to eliminate their processes with the longest cycle time. (These processes should be unfamiliar to you and should drive unfamiliar technology work.) Or, offer a new service to help them eliminate a problem supplier. Or provide them process data or information that helps them be more productive. Or, change how you make the product or how you stock/ship it to help your customer reduce inventory and respond faster.

Constrain the inputs. Reduce by 90% the required inputs to your product and reinvent it. The best example is electrical power. Give your engineers a radically lower power budget and tell them to provide as much goodness as possible. The result will be less goodness and a whole lot less power consumption. This could allow you to sell products to people with poor utilities (developing world) or help companies reduce their carbon footprint. (Isn’t that a nice value proposition these days.)

Make it more portable. If your product weighs tons, think pounds; if it weighs pounds, think ounces. If its size is measured in meters, think millimeters; if millimeters, think micrometers. The key here is to strip out functions and goodness so you can make it portable. Give ground on the crusty value proposition to sprout a new one.

These are just a few of the lenses, and you should use your deep knowledge and context to come up with the right ones for you. Here’s a neat exercise – ask your sales people how they’d sell your product without using your existing value proposition, then reimagine the product so they can sell it that way.

Your existing value proposition isn’t bad – it pays the bills and it’s what got you here, and, it’s what pays for creating the next generation of value propositions. What’s unskillful is thinking it will last forever.

Now is the only time you can shape your future. It’s time to disrupt yourself.

The Holy Grail of marketing is to identify emerging customer needs before anyone else and satisfy them to create new markets. It has been a long and fruitless slog as emerging needs have proven themselves elusive. And once candidates are identified, it’s a challenge to agree which are the game-changers and which are the ghosts. There are too many opinions and too few facts. But there’s treasure at the end of the rainbow and the quest continues.

Emerging things are just coming to be, just starting, so they appy to just a small subset of customers; and emerging things are new and different, so they’re unfamiliar. Unfamiliar plus small same size equals elusive.

I don’t believe in emerging customer needs, I believe in emergent customer behavior.

Emergent behavior is based on actions taken (past tense) and is objectively verifiable. Yes or no, did the customer use the product in a new way? Yes or no, did the customer make the product do something it wasn’t supposed to? Did they use it in a new industry? Did they modify the product on their own? Did they combine it with something altogether unrelated? No argument.

When you ask a customer how to improve your product, their answers aren’t all that important to them. But when a customer takes initiative and action, when they do something new and different with your product, it’s important to them. And even when just a few rouge customers take similar action, it’s worth understanding why they did it – there’s a good chance there’s treasure at the end of that rainbow.

With traditional VOC methods, it has been cost prohibitive to visit enough customers to learn about a handful at the fringes doing the same crazy new thing with your product. Also, with traditional VOCs, these “outliers” are thrown out because they’re, well, they’re outliers. But emergent behavior comes from these very outliers. New information streams and new ways to visualize them are needed to meet these challenges.

For these new information streams, think VOC without the travel; VOC without leading the witness; VOC where the cost of capturing their stories is so low there are so many stories captured that it’s possible to collect a handful of outliers doing what could be the seed for the next new market.

To reduce the cost of acquisition, stories are entered using an app on a smart phone; to let emergent themes emerge, customers code their own stories with a common, non-biasing set of attributes; and to see patterns and outliers, the coded stories are displayed visually.

In the past, the mechanisms to collect and process these information streams did not exist. But they do now.

I hope you haven’t given up on the possibility of understanding what your customers will want in the near future, because it’s now possible.

There are many flavors of innovation – incremental, disruptive, and seven flavors in between. And there is lots of argument about the level of innovation – mine’s radical and yours isn’t; that’s just improving what we already have; that’s too new – no one will ever buy it. We want to label the work in order to put it in the right bucket, to judge if we’re doing the right work. But the labels get in the way – they’re loaded with judgments, both purrs and snarls.

Truth is, innovation work falls on a continuum of newness and grouping them makes little sense. And, it’s not just newness that matters – it’s how the newness fits (or doesn’t) within the context of how things happen today and how customers think they should happen tomorrow. So what to do?

Customers notice the most meaningful innovations, and they notice the most meaningful ones before the less meaningful. Evaluate the time it takes a customer to notice the innovation and there may be hope to evaluate the importance of the innovation.

The technology reduces cost, and at the end of the month when the numbers are rolled up the accountants can see the improvement. This is real improvement, but there’s a significant lag and the people doing the work don’t see it as meaningful. This one’s a tough sell – buy this new thing, train on it, use it for three months, and if you keep good records and do some nifty statistics you’ll see an improvement.

The technology reduces scrap, and at the end of the week the scrap bin will be half full instead of fully full. Scrap is waste and waste reduction is real improvement. This is an easier sell – buy it and train on it and at the end of the week you’ll notice a reduction in scrap. This is important but only to those who are measured on scrap. And today the scrap is emptied every week, now we can empty it every other week. The time to notice is reduced, but the impact may not be there.

The technology increases throughput, and at the end of the shift the bins will be fuller than full. Here – try it for a shift and see what you think. If you like it, you can buy it. I’ll be back tomorrow with a quote. This is noticeable within eight hours. And at the end of eight hours there are more things that can be sold. That’s real money, and real money gets noticed.

The technology makes the product last two hours instead of one. Here – try it for a couple hours. I’ll go get a coffee and come back and see what you think. You won’t have to stop the machine nearly as often and you’ll put more parts into finished goods inventory. The technology gets noticed within two hours and the purchase order is signed in three.

Where the old technology was load, this is quiet. Don’t bother with ear protection, just give it a go. Pretty cool, isn’t it. Go get your boss and I’ll sell you a couple units right now. This one shows its benefits the end user right away – first try.

The most meaningful innovations get noticed instantly. Stop trying to label the innovation and simply measure how long it takes your customer to notice.